Tomato disease recognition using a compact convolutional neural network E ÖZBİLGE, MK ULUKÖK, Ö TOYGAR, E OZBILGE IEEE Access 10, 77213-77224, 2022 | 23 | 2022 |
On-line expectation-based novelty detection for mobile robots E Özbilge Robotics and Autonomous Systems 81, 33-47, 2016 | 9 | 2016 |
Artificial Intelligence-Assisted RT-PCR Detection Model for Rapid and Reliable Diagnosis of COVID-19 E Özbilge, T Sanlidag, E Ozbilge, B Baddal Applied Sciences 12 (19), 9908, 2022 | 6 | 2022 |
Experiments in online expectation-based novelty-detection using 3D shape and colour perceptions for mobile robot inspection E Özbilge Robotics and Autonomous Systems 117, 68-79, 2019 | 6 | 2019 |
Automated malaria parasite detection using artificial neural network E Özbilge, E Güler, M Güvenir, T Şanlıdağ, A Özbilgin, K Süer International Conference on Theory and Applications of Fuzzy Systems and …, 2020 | 5 | 2020 |
Determination of the unknown source function in time fractional parabolic equation with Dirichlet boundary conditions E Ozbilge, A Demir, F Kanca, E Özbilge Applied Mathematics & Information Sciences 10 (1), 283, 2016 | 5 | 2016 |
Inverse problem for a time fractional parabolic equation with nonlocal boundary conditions E Ozbilge, F Kanca, E Özbilge Mathematics 10 (9), 1479, 2022 | 4 | 2022 |
14th International Conference on Theory and Application of Fuzzy Systems and Soft Computing–ICAFS-2020 RA Aliev, J Kacprzyk, W Pedrycz, M Jamshidi, M Babanli, FM Sadikoglu Springer Nature, 2021 | 4 | 2021 |
Modelling and analysis of IoT technology using neural networks in agriculture environment E Özbilge, Y Kırsal, E Çaglar International Journal of Computers Communications & Control 15 (3), 2020 | 4 | 2020 |
Detecting static and dynamic novelties using dynamic neural network E Özbilge Procedia computer science 120, 877-886, 2017 | 2 | 2017 |
Skin Cancer Recognition Using Compact Deep Convolutional Neural Network AB FOFANAH, E ÖZBİLGE, Y KIRSAL Çukurova Üniversitesi Mühendislik Fakültesi Dergisi 38 (3), 787-797, 2023 | 1 | 2023 |
Expectation-Based Novelty Detection in Mobile Robotics E Özbilge, U Nehmzow, J Condell Towards Autonomous Robotic Systems: 10th Annual Conference, TAROS 2009, 210-215, 2009 | 1 | 2009 |
An MCDM Approach on Einstein Aggregation Operators under Bipolar Linear Diophantine Fuzzy Hypersoft Set SN Sri, J Vimala, N Kausar, E Ozbilge, E Özbilge, D Pamucar Heliyon, 2024 | | 2024 |
Extending the concepts of complex interval valued neutrosophic subbisemiring of bisemiring M Palanikumar, N Kausar, E Ozbilge, E Ozbilge International Journal of Neutrosophic Science 23 (4), 117-17-135, 2024 | | 2024 |
Fusion of Novelty Detectors Using Deep and Local Invariant Visual Features for Inspection Task E Özbilge, E Ozbilge IEEE Access 10, 121032-121047, 2022 | | 2022 |
Analysis and Modelling of Meteorological Sensory Signals for One-Hour-Ahead Wind Speed Forecasting using Dynamic Neural Networks E Özbilge, Y Kirsal 2022 30th Signal Processing and Communications Applications Conference (SIU …, 2022 | | 2022 |
Plant Disease Identification Through Deep Learning Ö Toygar, MK Ulukök, E Özbilge International Conference on Advanced Engineering, Technology and …, 2021 | | 2021 |
Expectation-based novelty detection for mobile robots E Özbilge University of Ulster, 2013 | | 2013 |
MartinMcGinnity Intelligent Systems Research Centre, University of Ulster D Bridge, K Brown, A Cater, S Coleman, LC Lero, N Creaney, F Cummins, ... | | 2011 |
Novelty Detection for Autonomous Inspection Robot in Dynamic Environment E Özbilge, TM McGinnity, J Condell MartinMcGinnity Intelligent Systems Research Centre, University of Ulster, 2011 | | 2011 |